You’re drowning in data.
But your data isn’t even worth drowning in. It’s inconsistent, unreliable, and untrustworthy—so what’s the point?
You need to get to trusted data. But getting there isn’t easy. It takes a lot of work, time, and money—especially when you don’t have the right tools to help you along the way.
That’s why we’ve created this technical solution workbook: “5 Steps to Successfully Deliver Adaptive Data & Analytics Governance.” In it, we walk you through exactly how to get to trusted data.
You’ll learn how to:
- Take back control of your data landscape by providing full visibility across all of your data assets
- Streamline processes and tasks with configurable workflows and automation
- Reduce data and compliance risks to set your organization up for success
Why you need adaptive data and analytics governance
At Colibra, we believe data governance is fundamental to a successful data management strategy. We also believe that your data governance model must be flexible, able to adapt to the evolving data needs of your organization.
Adaptive data and analytics governance recognizes and expands the role of data governance in driving business value. It is context-aware, promoting flexible decision-making and informed business outcomes. And unlike traditional data governance, adaptive data and analytics governance focuses on managing and organizing data and processes to enable collaboration and compliant access to produce insightful business-driving outcomes.
While maintaining strict adherence to regulation, security and privacy, adaptive data and analytics governance moves the focus off IT control, and fosters collaboration between technology groups, data owners and the business consumers of the data.
By giving the keys to the analysts and business users, adaptive data and analytics places the data in the hands of the people driving the business decisions, allowing them to innovate and create relevant and revelatory new tools and analysis. It democratizes the data and unlocks its latent value
However, while everyone acknowledges the value of data —according to the recent 2022 Data Intelligence Index from Collibra and IDC — most organizations face real challenges driving widespread adoption of data intelligence, including data governance. It’s a critical distinction that often differentiates leaders from laggards in our data-driven digital economy.
Why Collibra adaptive data and analytics governance
In a world where outcomes are critical, and scalability is essential, governance takes on even greater urgency. Coined by Gartner, adaptive data and analytics governance emphasizes the need to go beyond control and compliance to focus on business outcomes.
At Colibra, we believe adaptive data and analytics governance is essential to driving data intelligence. And we believe it’s the next big step forward in data governance.
A scalable solution, Collibra Adaptive Data and Analytics Governance delivers all the capabilities you need to take back control of your data landscape, improve the efficiency of your people and processes, and reduce your data and compliance risks.
Collibra Adaptive Data and Analytics Governance helps create a culture of trusted data that fuels better decision-making by:
- Bringing metadata into one central location via native integrations and APIs to important data sources, business applications, data science and BI tools so that data is available and easily accessible across your organization.
- Documenting definitions and ownership, certifying data assets, and capturing crowdsourced feedback, so users feel confident in using the data and empowered to make business decisions.
- Offering a single, scalable solution that includes all of the data catalog and governance capabilities you need to ensure your data is accurate, consistent, complete, and discoverable.
A step-by-step guide to adaptive data and analytics governance
You can start charting a path to data intelligence. Our new workbook gives you a step-by-step guide to reaching adaptive data governance, offering insights into:
- Aligning stakeholders
- Preparing your data catalog
- Establishing data lineage and a glossary
- Refining the operating model
- Defining data policies
Are you ready to stop drowning and start trusting your data?
